Comparison of multimodel ensembles of global and regional climate models projections for extreme precipitation over four major river basins in southern Africa— assessment of the historical simulations

Abstract

This study assesses the performance of large ensembles of global (CMIP5, CMIP6) and regional (CORDEX, CORE) climate models in simulating extreme precipitation over four major river basins (Limpopo, Okavango, Orange, and Zambezi) in southern Africa during the period 1983–2005. The ability of the model ensembles to simulate seasonal extreme precipitation indices is assessed using three high-resolution satellite-based datasets. The results show that all ensembles overestimate the annual cycle of mean precipitation over all basins, although the intermodel spread is large, with CORDEX being the closest to the observed values. Generally, all ensembles overestimate the mean and interannual variability of rainy days (RR1), maximum consecutive wet days (CWD), and heavy and very heavy precipitation days (R10mm and R20mm, respectively) over all basins during all three seasons. Simple daily rainfall intensity (SDII) and the number of consecutive dry days (CDD) are generally underestimated. The lowest Taylor skill scores (TSS) and spatial correlation coefficients (SCC) are depicted for CDD over Limpopo compared with the other indices and basins, respectively. Additionally, the ensembles exhibit the highest normalized standard deviations (NSD) for CWD compared to other indices. The intermodel spread and performance of the RCM ensembles are lower and better, respectively, than those of GCM ensembles (except for the interannual variability of CDD). In particular, CORDEX performs better than CORE in simulating extreme precipitation over all basins. Although the ensemble biases are often within the range of observations, the statistically significant wet biases shown by all ensembles underline the need for bias correction when using these ensembles in impact assessments.

Assessing Future Precipitation Patterns, Extremes and Variability in Major Nile Basin Cities: An Ensemble Approach with CORDEX CORE Regional Climate Models

“…These results support the findings of earlier studies on the severe rainfall indices in various regions of Africa. Positive trends in RX1Day, RX5Day, and CDD, and negative trends on consecutive wet days (CWD) are like those reported in East Africa and Ethiopia by [24], Central Africa [76], West Africa [77], Southern Africa [78], and over the Mediterranean and Sahara regions [79].…”

Exploring the Influence of Improved Horizontal Resolution on Extreme Precipitation in Southern Africa Major River Basins: Insights from CMIP6 HighResMIP Simulations

“…The DJF season is chosen since the region receives most of its precipitation during this period (Rouault et al 2024). In addition, previous research (Samuel et al 2023a) on the same basins indicated that model biases are more pronounced during the DJF period than during other seasons.…”

“…A notable constraint in the assessment of climate model simulations in Africa is the lack of reliable gauge-based observational datasets (Samuel et al 2023a;Weber et al 2023;Tamoffo et al 2023;Dosio et al 2022). Previous studies (Alexander et al 2020;Dosio et al 2021a;Faye and Akinsanola, 2022;Samuel et al 2022) have identified significant inconsistencies among gridded datasets across Africa.…”

“…The dataset is distinctive in that it combines multiple data sources from satellites, reanalysis, and rain gauge datasets to produce reliable estimates of precipitation across the entire globe (Beck et al 2019). Previous studies (Ilori and Balogun, 2021;Bador et al 2023;Liu et al 2023;Samuel et al 2023a) have used an ensemble of several observations from multiple sources as a reference for model evaluation in simulating precipitation characteristics.…”

“…The datasets used in this study have been utilized in previous works to assess the performance of climate models in reproducing precipitation (Samuel et al 2022;Moradian et at. 2023;Gnitou et al 2023;Samuel et al 2023a).…”